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High performance computing on complex environments
Published 2014Table of Contents: “…Chapter 4: Parallel Algorithms for Parabolic Problems on Graphs in Neuroscience4.1 Introduction; 4.2 Formulation of the Discrete Model; 4.3 Parallel Algorithms; 4.4 Computational Results; 4.5 Conclusions; Acknowledgments; References; Part III: Communication and Storage Considerations in High-Performance Computing; Chapter 5: An Overview of Topology Mapping Algorithms and Techniques in High-Performance Computing; 5.1 Introduction; 5.2 General Overview; 5.3 Formalization of the Problem; 5.4 Algorithmic Strategies for Topology Mapping; 5.5 Mapping Enforcement Techniques; 5.6 Survey of Solutions.…”
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Electronic eBook -
163
Robot Intelligence for Coordinated Manipulation and Its Industrial Application.
Published 2020Table of Contents: “…ASPW-DRL: assembly sequence planning for workpieces via a deep reinforcement learning approach -- Cooperative multi-agent search using Bayesian approach with connectivity maintenance -- An extended DMP framework for robot learning and improving variable stiffness manipulation -- Cooperative control of dual-arm robots in different human-robot collaborative tasks -- Reinforcement learning for human-robot shared control -- On stability for learning human control strategy by demonstrations using SVM -- A novel active balance assistive control strategy based on virtual stiffness model of XCoM…”
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eBook -
164
Materials Science and Intelligent Technologies Applications : Selected, Peer Reviewed Papers from the 2014 3rd International Conference on Key Engineering Materials and Computer Sc...
Published 2014Table of Contents: “…Automatic Badminton Action Recognition Using RGB-D SensorKinect-Based Badminton Action Analysis System; A Review of Hot Topic Detection and Tracking Technology; Study on the Improvement of TFIDF Algorithm in Data Mining; A New Protocol for Secure Distributed Multiplication of Two Polynomial Shared Values; Human Posture Recognition Based on DAG-SVMS; The Design and Implementation of Astronomical Multi-Catalog Storage and Cross-Match Based on Hadoop; The Multi-Scale Hough Transform Lane Detection Method Based on the Algorithm of Otsu and Canny; Design of Heart Sound Analyzer.…”
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Electronic Conference Proceeding eBook -
165
Accelerating MATLAB with GPU computing : a primer with examples
Published 2014Full text (MFA users only)
Electronic eBook -
166
Parallel Computing : Advances and Current Issues, Proceedings of the International Conference Parco2001.
Published 2002Table of Contents: “…Committees ; Preface ; Invited Papers ; Deploying Parallel Numerical Library Routines to Cluster Computing in a Self Adapting Fashion ; 1 Overview ; 2 Numerical libraries in shared homogeneous distributed environments ; 3 Sample software implementation and results.…”
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167
Iterative learning control for multi-agent systems coordination
Published 2017Full text (MFA users only)
Electronic eBook -
168
Advances in time series forecasting. Volume 2
Published 2017Table of Contents: “…INTRODUCTION -- CLASSICAL TIME SERIES FORECASTING MODELS -- ARTIFICIAL NEURAL NETWORKS FOR FORECASTING TIME SERIES -- A NEW ARTIFICIAL NEURAL NETWORK WITH DETERMINISTIC COMPONENTS -- APPLICATIONS -- CONCLUSION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES -- A Fuzzy Time Series Approach Based on Genetic Algorithm with Single Analysis Process -- Ozge Cagcag Yolcu* -- INTRODUCTION -- FUZZY TIME SERIES -- RELATED METHODS -- Genetic Algorithm (GA) -- Single Multiplicative Neuron Model -- PROPOSED METHOD -- APPLICATIONS -- CONCLUSION AND DISCUSSION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES -- Forecasting Stock Exchanges with Fuzzy Time Series Approach Based on Markov Chain Transition Matrix -- Cagdas Hakan Aladag1,* and Hilal Guney2 -- INTRODUCTION -- FUZZY TIME SERIES -- TSAUR 'S FUZZY TIME SERIES MARKOV CHAIN MODEL -- THE IMPLEMENTATION -- CONCLUSION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES -- A New High Order Multivariate Fuzzy Time Series Forecasting Model -- Ufuk Yolcu* -- INTRODUCTION -- RELATED METHODOLOGY -- The Fuzzy C-Means (FCM) Clustering Method -- Single Multiplicative Neuron Model Artificial Neural Network (SMN-ANN) -- Fuzzy Time Series -- THE PROPOSED METHOD -- APPLICATIONS -- CONCLUSIONS AND DISCUSSION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES -- Fuzzy Functions Approach for Time Series Forecasting -- Ali Z. …”
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169
Scientific computing with multicore and accelerators
Published 2010Full text (MFA users only)
Electronic eBook -
170
Stochastic Models in Reliability Engineering.
Published 2020Table of Contents: “…4.3.1 Run and Phrase -- 4.3.2 Multi-State Compression Algorithm -- 4.4 Proposed Multi-State Inference Algorithm -- 4.4.1 Rules for Calculating Intermediate Variables -- 4.4.2 Proposed Multi-State Inference Algorithm -- 4.5 Case Study -- 4.5.1 Case Background -- 4.5.2 Calculation and Analysis -- 4.6 Summary -- Appendix A -- Appendix B -- References -- Chapter 5 Reliability Analysis of Demand-Based Warm Standby System with Multi-State Common Bus -- 5.1 Introduction -- 5.2 Model Description for a DBWSS with Multi-State Common Bus Performance Sharing…”
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171
Empirical model building : data, models, and reality
Published 2011Table of Contents: “…Modular Data-Based Wargaming; 2.3.1. Herman Kahn and the Winning of the Cold War.…”
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172
PRINCIPLES OF QUANTUM ARTIFICIAL INTELLIGENCE.
Published 2013Table of Contents: “…Computation; 2.1 Entscheidungsproblem; 2.1.1 Cantor's diagonal argument; 2.1.2 Reductio ad absurdum; 2.2 Complexity Theory; 2.2.1 Decision problems; 2.2.2 P and NP; 2.3 Church-Turing Thesis; 2.3.1 Church-Turing-Deutsch principle; 2.4 Computers; 2.4.1 Analog computers; 2.4.2 Digital computers; 2.4.3 Von Neumann architecture; 3. …”
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173
Hands-On Blockchain with Hyperledger : Building Decentralized Applications with Hyperledger Fabric and Composer.
Published 2018Table of Contents: “…Decentralization with systemic governanceEnterprise support; Use case-driven pluggability choices; Shared ledger technology; Consensus; Crypto algorithms and encryption technology; Use case-driven pluggable choices; Enterprise integration and designing for extensibility; Other considerations; Consensus, ACID property, and CAP; CAP; ACID; Attestation -- SSCs are signed and encrypted; Use of HSMs; Summary; Chapter 2: Exploring Hyperledger Fabric; Building on the foundations of open computing; Fundamentals of the Hyperledger project; The Linux Foundation ; Hyperledger.…”
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174
Methods and Interdisciplinarity
Published 2020Table of Contents: “…Towards a win-win collaboration; 2.3.3. Geography in all digital objects; 2.4. …”
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175
Goliath's revenge : how established companies turn the tables on digital disruptors
Published 2019Table of Contents: “…Chapter 6 Rule 3: Use Your Data as CurrencySome Historical Context; Entertainment Goes Left Brain; Moneyball Wins Games; Build Your Data Balance Sheet; Think Broadly about Your Data Assets; Understand Your Data Liabilities; Rate the Quality of Each Data Asset; Pay Special Attention to the Edge; Value Data Optionality; Maximize Return on Data; Digital Customer Segments; Master Machine Learning; The Weather Channel; Rule 3: Company and Career Readiness; Company Readiness Self-Assessment; Career Readiness Self-Assessment; Rule 3 Readiness Summary; Note…”
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176
Cognitive Electronic Warfare : An Artificial Intelligence Approach.
Published 2021Table of Contents: “…-- 1.5 Reader's Guide -- 1.6 Conclusion -- References -- 2 Objective Function -- 2.1 Observables That Describe the Environment -- 2.1.1 Clustering Environments -- 2.2 Control Parameters to Change Behavior -- 2.3 Metrics to Evaluate Performance -- 2.4 Creating a Utility Function -- 2.5 Utility Function Design Considerations -- 2.6 Conclusion -- References -- 3 ML Primer -- 3.1 Common ML Algorithms -- 3.1.1 SVMs -- 3.1.2 ANNs -- 3.2 Ensemble Methods -- 3.3 Hybrid ML -- 3.4 Open-Set Classification -- 3.5 Generalization and Meta-learning -- 3.6 Algorithmic Trade-Offs -- 3.7 Conclusion -- References -- 4 Electronic Support -- 4.1 Emitter Classification and Characterization -- 4.1.1 Feature Engineering and Behavior Characterization -- 4.1.2 Waveform Classification -- 4.1.3 SEI -- 4.2 Performance Estimation -- 4.3 Multi-Intelligence Data Fusion -- 4.3.1 Data Fusion Approaches -- 4.3.2 Example: 5G Multi-INT Data Fusion for Localization -- 4.3.3 Distributed-Data Fusion -- 4.4 Anomaly Detection -- 4.5 Causal Relationships -- 4.6 Intent Recognition -- 4.6.1 Automatic Target Recognition and Tracking -- 4.7 Conclusion -- References -- 5 EP and EA -- 5.1 Optimization -- 5.1.1 Multi-Objective Optimization -- 5.1.2 Searching Through the Performance Landscape -- 5.1.3 Optimization Metalearning -- 5.2 Scheduling -- 5.3 Anytime Algorithms -- 5.4 Distributed Optimization -- 5.5 Conclusion.…”
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177
Pulmonary arterial hypertension : diagnosis and evidence-based treatment
Published 2008Table of Contents: “…Combination therapy in pulmonary arterial hypertension / Anne Keogh and Marius Hoeper -- Interventional and surgical modalities of treatment for pulmonary arterial hypertension / Julio Sandoval and Ramona Doyle -- End points and clinical trial design in pulmonary arterial hypertension : clinical and regulatory perspectives / Andrew J. …”
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178
Code : Collaborative Ownership and the Digital Economy.
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179
Pattern Recognition in Computational Molecular Biology : Techniques and Approaches
Published 2015Full text (MFA users only)
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180
Mechanisms and games for dynamic spectrum allocation
Published 2013Table of Contents: “…7.3.10 Other equilibrium concepts -- 7.4 Learning equilibria -- 7.4.1 Learning Nash equilibria -- 7.4.2 Learning epsilon-equilibrium -- 7.4.3 Learning coarse correlated equilibrium -- 7.4.4 Learning satisfaction equilibrium -- 7.4.5 Discussion -- 7.5 Conclusion -- References -- II Cognitive radio and sharing of unlicensed spectrum -- 8 Cooperation in cognitiveradio networks: from accessto monitoring -- 8.1 Introduction -- 8.1.1 Cooperation in cognitive radio: mutual benefits and costs -- 8.2 An overview of coalitional game theory -- 8.3 Cooperative spectrum exploration and exploitation -- 8.3.1 Motivation -- 8.3.2 Basic problem -- 8.3.3 Joint sensing and access as a cooperative game -- 8.3.4 Coalition formation algorithm for joint sensing and access -- 8.3.5 Numerical results -- 8.4 Cooperative primary user activity monitoring -- 8.4.1 Motivation -- 8.4.2 Primary user activity monitoring: basic model -- 8.4.3 Cooperative primary user monitoring -- 8.4.4 Numerical results -- 8.5 Summary -- Acknowledgements -- Copyright notice -- References -- 9 Cooperative cognitive radios with diffusion networks -- 9.1 Introduction -- 9.2 Preliminaries -- 9.2.1 Basic tools in convex and matrix analysis -- 9.2.2 Graphs -- 9.3 Distributed spectrum sensing -- 9.4 Iterative consensus-based approaches -- 9.4.1 Average consensus algorithms -- 9.4.2 Acceleration techniques for iterative consensus algorithms -- 9.4.3 Empirical evaluation -- 9.5 Consensus techniques based on CoMAC -- 9.6 Adaptive distributed spectrum sensing based on adaptive subgradient techniques -- 9.6.1 Distributed detection with adaptive filters -- 9.6.2 Set-theoretic adaptive filters for distributed detection -- 9.6.3 Empirical evaluation -- 9.7 Channel probing -- 9.7.1 Introduction -- 9.7.2 Admissibility problem -- 9.7.3 Power and admission control algorithms.…”
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